Yudong Liang

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This paper proposes a novel neural network learning the essential mapping function between the low resolution and high resolution image for Image superresolution problem. In our approach, patch recurrence property of small patches in natural image are utilized as a prior to train the network. An autoencoder neutral network is designed to reconstruct the(More)
Learning the non-linear image upscaling process has previously been considered as a simple regression process, where various models have been utilized to describe the correlations between high-resolution (HR) and low-resolution (LR) images/patches. In this paper, we present a multitask learning framework based on deep neural network for image(More)
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